Linear Regression Model (LR)

(LR-1) Describe your topic, provide your data, and cite your source. Collect at least 8 data poin" rel="nofollow">ints. Label appropriately. The idea with the discussion postin" rel="nofollow">ing is two-fold: (1) To share your in" rel="nofollow">interestin" rel="nofollow">ing project idea with your classmates, and (2) To give me a chance to give you a brief thumbs-up or thumbs-down about your proposed topic and data. Sometimes students get off on the wrong foot or misunderstand the in" rel="nofollow">intent of the project, and your postin" rel="nofollow">ing provides an opportunity for some feedback. Remark: Students may choose similar topics, but must have different data sets. For example, several students may be in" rel="nofollow">interested in" rel="nofollow">in a particular Olympic sport, and that is fin" rel="nofollow">ine, but they must collect different data, perhaps from different events or different gender. (LR-2) Plot the poin" rel="nofollow">ints (x, y) to obtain" rel="nofollow">in a scatterplot. Use an appropriate scale on the horizontal and vertical axes and be sure to label carefully. Visually judge whether the data poin" rel="nofollow">ints exhibit a relatively lin" rel="nofollow">inear trend. (If so, proceed. If not, try a different topic or data set.) (LR-3) Fin" rel="nofollow">ind the lin" rel="nofollow">ine of best fit (regression lin" rel="nofollow">ine) and graph it on the scatterplot. State the equation of the lin" rel="nofollow">ine. (LR-4) State the slope of the lin" rel="nofollow">ine of best fit. Carefully in" rel="nofollow">interpret the meanin" rel="nofollow">ing of the slope in" rel="nofollow">in a sentence or two. (LR-5) Fin" rel="nofollow">ind and state the value of r2, the coefficient of determin" rel="nofollow">ination, and r, the correlation coefficient. Discuss your fin" rel="nofollow">indin" rel="nofollow">ings in" rel="nofollow">in a few sentences. Is r positive or negative? Why? Is a lin" rel="nofollow">ine a good curve to fit to this data? Why or why not? Is the lin" rel="nofollow">inear relationship very strong, moderately strong, weak, or nonexistent? (LR-6) Choose a value of in" rel="nofollow">interest and use the lin" rel="nofollow">ine of best fit to make an estimate or prediction. Show calculation work. (LR-7) Write a brief narrative of a paragraph or two. Summarize your fin" rel="nofollow">indin" rel="nofollow">ings and be sure to mention any aspect of the lin" rel="nofollow">inear model project (topic, data, scatterplot, lin" rel="nofollow">ine, r, or estimate, etc.) that you found particularly important or in" rel="nofollow">interestin" rel="nofollow">ing.